The following explanations of terms are first given in order to introduce to the present invention.
“Web services” (sometimes called application services) are services (usually including some combination of programming and data, but possibly including human resources as well) that are made available from a business's Web server for Web users or other Web-connected programs. Providers of Web services are generally known as application service providers. Web services range from such major services as storage management and customer relationship management (CRM) down to much more limited services such as the furnishing of a stock quote and the checking of bids for an auction item. The accelerating creation and availability of these services is a major Web trend.
Users can access some Web services through a peer-to-peer arrangement rather than by going to a central server. Some services can communicate with other services and this exchange of procedures and data is generally enabled by a class of software known as middleware. Services previously possible only with the older standardized service known as Electronic Data Interchange (EDI) increasingly are likely to become Web services. Besides the standardization and wide availability to users and businesses of the Internet itself, Web services are also increasingly enabled by the use of the Extensible Markup Language (XML) as a means of standardizing data formats and exchanging data. XML is the foundation for the Web Services Description Language (WDSL).
Message broker: In a telecommunication network, where programs communicate by exchanging formally-defined messages (that is, through the act of messaging), a message broker is an intermediary program that translates a message from the formal messaging protocol of the sender to the formal messaging protocol of the receiver. Message broker programs are sometimes known as middleware.
Autonomic Management:
Autonomic management is regarded as a next evolution step on top of the preceding challenges in the field of complexity of system control, resource sharing, and operational management. Autonomic management techniques do disadvantageously not address a cooperation of stateful dynamic instances, virtualized services and operational message stores on customer's request, which would be useful in the field of on-demand computing.
Virtualized services: Virtualized services can be viewed as a pool of server resources from which private, secured configurations can be dynamically allocated to support an application and then disbanded if necessary. With this approach, server capacity no longer must be dedicated to individual applications, and services are not tied to specific hardware or network-paths. As a result, clients pay only for the resources they utilize and have access to powerful features such as high availability, disaster recovery and real-time scalability without the expensive over-provisioning required by legacy systems.
Known systems do not provide autonomic management facilities such as a Monitor, Analyze, Plan, and Execute (MAPE) capability. The dynamic allocation of resources is disadvantageously not fully automated and requires human intervention.
Dynamic Instances:
The Web service (WS)-Resource construct is considered to concentrate on means to express the relationship between stateful resources and Web services. The known service includes neither the necessary techniques for autonomic management nor the operation of operational message stores, which would be useful in the field of on-demand computing.
In the before-mentioned field the present invention has special applicability to a networked environment, wherein response time must be reliably short, system availability must be guaranteed, and wherein a large range of message throughput is realized in order to do the required business. A good example relates to financial services offered via Web Services in an information technology (IT) environment, the basic system structure of which is schematically depicted in FIG. 1.
A number of custom applications 110, 112, 114 connect to a bank house's business resources. They are used to provide the user requests to the bank's IT environment for performing the requested user services, like money transfer, trade of shares, etc. via inclusion of a secure banking network 150 connecting to other banks and trade institutions. The banking system environment is depicted in the central portion 102 of the drawing.
Such environment comprises a message broker environment having associated a number of network-connected services 106, which are realized by specific respective message flows. Examples are funds transfer services. Security-con trolling services, Bank-to-bank messaging. The before-mentioned business applications access the services via predefined software interfaces, comprising the management of requests via prior art queue management. This messaging middleware is controlled in latest prior art by means of some middleware interfaced between applications and operating system.
In the known prior art, such middleware defines how many resources 104 are usable for satisfying a given need of traffic involved by the business's peak loads. The peak load determines the number of pre-allocated resources needed to perform the desired services according to the rules defined in a pre-defined schedule of Quality of Service (QoS). Such schedule might contain the following basic rules and requirements, as they are known from electronic banking prior art. An exemplary rule derived from common heuristics in the electronic banking domain is a calendar schedule. Two variants of this approach might be:                3. Annual closing of account:                    Number of online transactions per minute: >800                        4. Quarterly closing of account:                    Number of online transactions per minute: >800                        
For example a maximum number of hardware servers offering a given need of CPU-power and disk storage capacity are pre-occupied in order to run a respective maximum number of service instantiations for doing the business.
Accordingly, available processing resources must be dimensioned to accommodate peak workload requirements. As a result, resources are significantly over-provisioned to ensure message throughput and delivery of service with acceptable performance and availability characteristics. These resources are typically left unexploited during intervals of low to medium message traffic.
The disadvantage is that this rigid concept of static resource allocation does not flexibly respond to varying loads. Thus, in periods with light traffic, many hardware resources are bound, but they remain unused. Only in peak load periods good system efficiency prevails.